In business we typically measure a lot of things, but when it comes to financial information are we making and utilizing financial measurements that matter?

What Does That Mean?

To understand what I’m referring, let’s look back at the posting Some Key Financial Indicators where we briefly considered a few things to track in regards to the balance sheet, sales, income statement, and payroll and personnel. In that blog post were some items that can tell you a lot about how your business is performing. Now I want to focus on the quality of our financial measurements.

What Do I Mean by Quality?

When measuring sales data here are the things that were mentioned in that posting:

Sales pipeline. What is the status of potential sales? How far along the pipeline are sales leads?

Orders on hand. You must know this to be sure you have the resources to meet these obligations

Order backlog. Here I am referring primarily to orders which you cannot immediately fulfil. How long before you can fulfill? Is there an alternative acceptable to the customer if you cannot meet the original order?

Now there is nothing wrong with measuring any of these things, but that said there is an issue of the quality of these measurements. For example, let’s assume that the sales pipeline is full of strong potential orders, we have more than adequate orders on hand, and the order backlog is manageable. On the surface that all sounds great, right?

Now let look at a little more to see how the quality of this data determines if it is comprised of financial measurements that matter. Just because you have a strong sales pipeline, plenty of orders on hand, and a manageable order backlog doesn’t mean you have quality. Imagine upon further examination it is determined that a high percentage of the sales pipeline, orders on hand, and order backlog is for customers who traditionally are slow to pay, products that are low margin, or both, Suddenly, having plenty of orders doesn’t necessarily look as appealing. You may find your company working like crazy to meet demand, only to find out later that the actual profit is very low and even worse that the collection of accounts receivable is going to be very slow. Both will hurt your cash flow.

This deeper analysis of the quality of the data is important.

Understand What You Measure

I will offer one more example. Let’s say your measurement show a dramatic reduction in production time. If that comes with a reduction in quality it may be that the production time improvement is a bit misleading.

The bottom line here is that very few, if any, statistics should be considered alone. They are much more meaningful if they are interpreted in light of other statistics, data, and analysis.